nabqr: Python package for improving probabilistic forecasts
Machine Learning
2025-01-30 v1 Applications
Computation
Abstract
We introduce the open-source Python package NABQR: Neural Adaptive Basis for (time-adaptive) Quantile Regression that provides reliable probabilistic forecasts. NABQR corrects ensembles (scenarios) with LSTM networks and then applies time-adaptive quantile regression to the corrected ensembles to obtain improved and more reliable forecasts. With the suggested package, accuracy improvements of up to 40% in mean absolute terms can be achieved in day-ahead forecasting of onshore and offshore wind power production in Denmark.
Cite
@article{arxiv.2501.17604,
title = {nabqr: Python package for improving probabilistic forecasts},
author = {Bastian Schmidt Jørgensena and Jan Kloppenborg Møller and Peter Nystrup and Henrik Madsen},
journal= {arXiv preprint arXiv:2501.17604},
year = {2025}
}